Kinerja Logika Fuzzy Sugeno dalam Menangani Prediksi Kain Tenun dengan Kombinasi Random Tree dalam Membangun Rule - Tundo, Tundo (Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha, 2021)
This study describes the performance of Sugeno fuzzy logic in determining the amount of woven fabric production by using a combination of random tree decision trees in forming rules. The criteria used in determining the amount of production, namely, production costs, demand, and stock obtained from woven fabric entrepreneurs in Mlaki Wanarejan Utara Pemalang. The random tree decision tree is used, one of which is to automatically generate rules from the available data without consulting with experts, in addition to introducing random trees in the field of research because there are still few studies using this decision tree. The results of this study, it was found that the accuracy while the prediction results tested obtained an Average Forecasting Error Rate (AFER) of 42% with a value 58% truth after being compared with the actual production data.Keywords : Fuzzy Logic, Fuzzy Sugeno Method, Rule, Random tree, Prediction.